David Mallery

BACKGROUND: Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas. METHODS: We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes. RESULTS: Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma. CONCLUSIONS: The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.).

Purpose To compare the progression-free survival (PFS) using a treatment regimen selected by molecular profiling (MP) of a patient's tumor with the PFS for the most recent regimen on which the patient had experienced progression (ie, patient as his own control). Patients and Methods Patients with refractory metastatic cancer had tissue samples submitted for MP in two formats including formalin-fixed tissue for immunohistochemistry and fluorescent in situ hybridization assays and immediately frozen tissue for oligonucleotide microarray (MA) gene expression assays (all performed in a Clinical Laboratory Improvement Amendments [ CLIA ] –certified laboratory). The MP approach was deemed of clinical benefit for the individual patient who had a PFS ratio (PFS on MP-selected therapy/PFS on prior therapy) of ≥ 1.3. Results In 86 patients who had MP attempted, there was a molecular target detected in 84 (98%). Sixty-six of the 84 patients were treated according to MP results. Eighteen (27%) of 66 patients had a PFS ratio of ≥ 1.3 (95% CI, 17% to 38%; one-sided, one-sample P = .007). Therefore, the null hypothesis (that ≤ 15% of this patient population would have a PFS ratio of ≥ 1.3) was rejected. Conclusion It is possible to identify molecular targets in patients' tumors from nine different centers across the United States. In 27% of patients, the MP approach resulted in a longer PFS on an MP-suggested regimen than on the regimen on which the patient had just experienced progression. Issues to be considered in interpretation of this study include limited prior experience with patients as their own controls as a study end point and overall patient attrition.

BACKGROUND: Next generation sequencing tests (NGS) are usually performed on relatively small core biopsy or fine needle aspiration (FNA) samples. Data is limited on what amount of tumor by volume or minimum number of FNA passes are needed to yield sufficient material for running NGS. We sought to identify the amount of tumor for running the PCDx NGS platform. METHODS: 2,723 consecutive tumor tissues of all cancer types were queried and reviewed for inclusion. Information on tumor volume, success of performing NGS, and results of NGS were compiled. Assessment of sequence analysis, mutation calling and sensitivity, quality control, drug associations, and data aggregation and analysis were performed. RESULTS: 6.4% of samples were rejected from all testing due to insufficient tumor quantity. The number of genes with insufficient sensitivity make definitive mutation calls increased as the percentage of tumor decreased, reaching statistical significance below 5% tumor content. The number of drug associations also decreased with a lower percentage of tumor, but this difference only became significant between 1-3%. The number of drug associations did decrease with smaller tissue size as expected. Neither specimen size or percentage of tumor affected the ability to pass mRNA quality control. A tumor area of 10 mm2 provides a good margin of error for specimens to yield adequate drug association results. CONCLUSIONS: Specimen suitability remains a major obstacle to clinical NGS testing. We determined that PCR-based library creation methods allow the use of smaller specimens, and those with a lower percentage of tumor cells to be run on the PCDx NGS platform.

BACKGROUND: It is widely acknowledged that there is value in examining cancers for genomic aberrations via next-generation sequencing (NGS). How commercially available NGS platforms compare with each other, and the clinical utility of the reported actionable results, are not well known. During the course of the current study, the Foundation One (F1) test generated data on a combination of somatic mutations, insertion and deletion polymorphisms, chromosomal abnormalities, and deoxyribonucleic acid (DNA) copy number changes at ~250× coverage, while the Paradigm Cancer Diagnostic (PCDx) test generated the same type of data at >5,000× coverage, plus provided messenger RNA (mRNA) expression levels. We sought to compare and evaluate paired formalin-fixed paraffin-embedded tumor tissue using these two platforms. METHODS: Samples from patients with advanced solid tumors were submitted to both the F1 and PCDx vendors for NGS analysis. Turnaround time (TAT) was calculated. Biomarkers were considered clinically actionable if they had a published association with treatment response in humans and were assigned to the following categories: commercially available drug (CA), clinical trial drug (CT), or neither option (hereafter referred to as "None"). RESULTS: The demographics of the 21 unique patient tumor samples included ten men and eleven women, with a median age of 56 years. Due to insufficient archival tissue from the same collection period, in one case, we used samples from different collections. PCDx reported first results faster than F1 in 20 cases. When received at both vendors on the same day, PCDx reported first results for 14 of 15 cases, with a median TAT of 9 days earlier than F1 (P<0.0001). Categorization of CA compared to CT and none significantly favored PCDx (P=0.012). CONCLUSION: In the current analysis, commercially available NGS platforms provided clinically relevant actionable targets (CA or CT) in 47%-67% of diverse cancer types. In the samples analyzed, PCDx significantly outperformed F1 in TAT, and had statistically significant higher clinically relevant actionable targets categorized as CA.

Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (, , ) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types.